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Tiered Cloud Routing: Methodology, Latency, and Improvement

Publication ,  Journal Article
Lin, S; Zhou, Y; Zhang, X; Arnold, T; Govindan, R; Yang, X
Published in: Proceedings of the ACM on Measurement and Analysis of Computing Systems
March 10, 2025

Large cloud providers including AWS, Azure, and Google Cloud offer two tiers of network services to their customers: one class uses the providers' private wide area networks (WAN-transit) to carry a customer's traffic as much as possible, and the other uses the public internet (inet-transit). Little is known about how each cloud provider configures its network to offer different transit services, how well these services work, and whether the quality of those services can be further improved. In this work, we conduct a large-scale study to answer these questions. Using RIPE Atlas probes as vantage points, we explore how traffic enters and leaves each cloud's WAN. In addition, we measure the access latency of the WAN-transit and the inet-transit service of each cloud and compare it with that of an emulated performance-based routing strategy. Our study shows that despite the cloud providers' intention to carry customers' traffic on its WAN to the maximum extent possible, for about 12% (Azure) and 13% (Google) of our vantage points, traffic exits the cloud WAN early at cloud edges more than 5000km away from the vantage points' nearest cloud edges. In contrast, more than 84% (AWS), 78% (Azure), and 81% (Google) of vantage points enter a cloud WAN within a 500km radius of their respective locations. Moreover, we find that cloud providers employ different routing strategies to implement the inet-transit service, leading to transit policies that may deviate from their advertised service descriptions. Finally, we find that a performance-based routing strategy can significantly reduce latencies in all three cloud providers for 4% to 85% of vantage point and cloud region pairs.

Duke Scholars

Published In

Proceedings of the ACM on Measurement and Analysis of Computing Systems

DOI

EISSN

2476-1249

Publication Date

March 10, 2025

Volume

9

Issue

1
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Lin, S., Zhou, Y., Zhang, X., Arnold, T., Govindan, R., & Yang, X. (2025). Tiered Cloud Routing: Methodology, Latency, and Improvement. Proceedings of the ACM on Measurement and Analysis of Computing Systems, 9(1). https://doi.org/10.1145/3711705
Lin, S., Y. Zhou, X. Zhang, T. Arnold, R. Govindan, and X. Yang. “Tiered Cloud Routing: Methodology, Latency, and Improvement.” Proceedings of the ACM on Measurement and Analysis of Computing Systems 9, no. 1 (March 10, 2025). https://doi.org/10.1145/3711705.
Lin S, Zhou Y, Zhang X, Arnold T, Govindan R, Yang X. Tiered Cloud Routing: Methodology, Latency, and Improvement. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 2025 Mar 10;9(1).
Lin, S., et al. “Tiered Cloud Routing: Methodology, Latency, and Improvement.” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 9, no. 1, Mar. 2025. Scopus, doi:10.1145/3711705.
Lin S, Zhou Y, Zhang X, Arnold T, Govindan R, Yang X. Tiered Cloud Routing: Methodology, Latency, and Improvement. Proceedings of the ACM on Measurement and Analysis of Computing Systems. 2025 Mar 10;9(1).

Published In

Proceedings of the ACM on Measurement and Analysis of Computing Systems

DOI

EISSN

2476-1249

Publication Date

March 10, 2025

Volume

9

Issue

1